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Using artificial intelligence for autonomous sensation analysis from audio data

Using artificial intelligence for autonomous sensation analysis from audio data - KIRun

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
DRKS
Registry ID
DRKS00025380
Enrollment
50
Registered
2021-06-21
Start date
2021-07-05
Completion date
Unknown
Last updated
2025-04-07

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

healthy subjects (sports ability according to PAR-Q must be given)

Interventions

Group 1: healthy runners
3-5 runs per subject on selected reference tracks (outdoor) or a treadmill (indoor)
during running, accelerometers on each tibia to measure biomechanical parameters (e.g. tibial shock, pronation), a chest strap to record heart rate, and an arm pocket with a smartphone that serves as

Sponsors

Universitätsklinikum Tübingen, Abt. Sportmedizin
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 60 Years

Inclusion criteria

Inclusion criteria: running beginners to ambitious recreational runners; can run at least 3 kilometers continuously (no walking or nordic walking); sports ability according to PAR-Q, good german language skills (information letter, profile questions, app instructions)

Exclusion criteria

Exclusion criteria: diseases of the musculoskeletal system for which medical treatment and a break from sports/running or reduction in sports/running activity is currently required; previous operations, injuries or diseases that impair current running activity; diseases that impair the ability to exercise in everyday life (query via PAR-Q, medical clearance may be required); current or chronic general infection; high blood pressure at rest >150/95 (medical clarification required, medical clearance may be required)

Design outcomes

Primary

MeasureTime frame
The primary objective is to use the system for a reliable, autonomous determination of the subjective and objective well-being of the athlete and to determine the optimal environmental parameters for this purpose.

Secondary

MeasureTime frame
During running, various training parameters, environmental conditions (e.g. identification of ground conditions by the audio signals of the running sound), biomechanical and physiological parameters as well as the subjective exertion perception are also recorded.

Countries

Germany

Contacts

Public ContactValerie Dieter

Universitätsklinikum Tübingen, Abt. Sportmedizin

valerie.dieter@med.uni-tuebingen.de0049-7071-2986477

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 4, 2026